{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<module 'acados' from '/home/amon/Repositories/l4acados/examples/l4casadi_vs_l4acados/acados.py'>"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import acados\n",
    "import importlib\n",
    "\n",
    "importlib.reload(acados)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "from acados import run, MultiLayerPerceptron, DoubleIntegratorWithLearnedDynamics, MPC\n",
    "import l4casadi as l4c\n",
    "import numpy as np\n",
    "import time\n",
    "import l4acados as l4a\n",
    "from typing import Optional, Union\n",
    "import torch\n",
    "import casadi as cs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "from l4acados.controllers.residual_learning_mpc import ResidualLearningMPC\n",
    "from l4acados.models import ResidualModel, PyTorchFeatureSelector\n",
    "from l4acados.controllers.zoro_acados_utils import setup_sim_from_ocp"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "import copy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "from run_single_experiment import *"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "N = 20\n",
    "ts = 1.0 / N\n",
    "batch_dim = 1\n",
    "hidden_layers = 5\n",
    "warmup_iter = 100\n",
    "solve_steps = 1000\n",
    "num_threads = 1\n",
    "# device = \"cpu\"\n",
    "device = \"cuda\"\n",
    "num_threads_acados_openmp = 4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[0mCMake Deprecation Warning at CMakeLists.txt:32 (cmake_minimum_required):\n",
      "  Compatibility with CMake < 3.10 will be removed from a future version of\n",
      "  CMake.\n",
      "\n",
      "  Update the VERSION argument <min> value.  Or, use the <min>...<max> syntax\n",
      "  to tell CMake that the project requires at least <min> but has been updated\n",
      "  to work with policies introduced by <max> or earlier.\n",
      "\n",
      "\u001b[0m\n",
      "\u001b[0mCMake Deprecation Warning at external/blasfeo/CMakeLists.txt:36 (cmake_minimum_required):\n",
      "  Compatibility with CMake < 3.10 will be removed from a future version of\n",
      "  CMake.\n",
      "\n",
      "  Update the VERSION argument <min> value.  Or, use the <min>...<max> syntax\n",
      "  to tell CMake that the project requires at least <min> but has been updated\n",
      "  to work with policies introduced by <max> or earlier.\n",
      "\n",
      "\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-- Build type is Release\n",
      "-- OpenMP_CXX_FLAGS: -fopenmp, OpenMP_C_FLAGS: -fopenmp\n",
      "-- Using linear algebra: HIGH_PERFORMANCE\n",
      "-- Using matrix format: PANELMAJ\n",
      "-- Using external BLAS: 0\n",
      "-- Testing target X64_INTEL_HASWELL: assembly compilation [success]\n",
      "-- Testing target X64_INTEL_HASWELL: assembly run [success]\n",
      "-- Testing target X64_INTEL_HASWELL: intrinsic compilation [success]\n",
      "-- Testing target X64_INTEL_HASWELL: intrinsic run [success]\n",
      "-- Detected target X64_INTEL_HASWELL\n",
      "-- Using BLASFEO path: \n",
      "-- Installation directory: /home/amon/Repositories/l4acados/external/acados\n",
      "--  \n",
      "-- Target: BLASFEO is X64_AUTOMATIC, HPIPM is X64_AUTOMATIC\n",
      "-- Linear algebra: HIGH_PERFORMANCE\n",
      "-- Octave MEX (OFF)\n",
      "-- System name:version Linux:6.9.3-76060903-generic\n",
      "-- Build type is Release\n",
      "-- Installation directory is /home/amon/Repositories/l4acados/external/acados\n",
      "-- OpenMP parallelization is ON\n",
      "-- Number of threads for acados with openMP (ACADOS_NUM_THREADS) 4\n",
      "--  \n",
      "-- Configuring done (0.3s)\n",
      "-- Generating done (0.0s)\n",
      "-- Build files have been written to: /home/amon/Repositories/l4acados/external/acados/build\n",
      "[ 33%] Built target blasfeo\n",
      "[ 34%] Built target getting_started\n",
      "[ 35%] Built target example_s_lu_factorization\n",
      "[ 36%] Built target example_d_lu_factorization\n",
      "[ 37%] Built target example_d_lq_factorization\n",
      "[ 38%] Built target example_d_riccati_recursion\n",
      "[ 39%] Built target example_s_riccati_recursion\n",
      "[ 80%] Built target hpipm\n",
      "[100%] Built target acados\n",
      "\u001b[36mInstall the project...\u001b[0m\n",
      "-- Install configuration: \"Release\"\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/lib/libacados.so\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/acados\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/acados/dense_qp\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/acados/dense_qp/dense_qp_qore.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/acados/dense_qp/dense_qp_qpoases.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/acados/dense_qp/dense_qp_ooqp.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/acados/dense_qp/dense_qp_common.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/acados/dense_qp/dense_qp_daqp.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/acados/dense_qp/dense_qp_hpipm.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/acados/utils\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/acados/utils/print.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/acados/utils/strsep.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/acados/utils/mem.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/acados/utils/timing.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/acados/utils/math.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/acados/utils/types.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/acados/utils/external_function_generic.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/acados/ocp_qp\n",
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      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/acados/ocp_qp/ocp_qp_qpdunes.h\n",
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      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/acados/ocp_qp/ocp_qp_partial_condensing.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/acados/sim\n",
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      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/cmake/acadosTargets-release.cmake\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/cmake/acadosConfig.cmake\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/acados_c\n",
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      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/acados_c/sim_interface.h\n",
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      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/acados_c/ocp_nlp_interface.h\n",
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      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_d_cast_qcqp.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_d_cond.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_d_cond_aux.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_d_cond_qcqp.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_d_core_qp_ipm.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_d_core_qp_ipm_aux.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_d_dense_qcqp.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_d_dense_qcqp_dim.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_d_dense_qcqp_ipm.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_d_dense_qcqp_res.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_d_dense_qcqp_sol.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_d_dense_qcqp_utils.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_d_dense_qp.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_d_dense_qp_dim.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_d_dense_qp_ipm.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_d_dense_qp_kkt.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_d_dense_qp_res.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_d_dense_qp_sol.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_d_dense_qp_utils.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_d_ocp_qcqp.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_d_ocp_qcqp_dim.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_d_ocp_qcqp_ipm.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_d_ocp_qcqp_red.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_d_ocp_qcqp_res.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_d_ocp_qcqp_sol.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_d_ocp_qcqp_utils.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_d_ocp_qp.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_d_ocp_qp_dim.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_d_ocp_qp_ipm.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_d_ocp_qp_kkt.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_d_ocp_qp_red.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_d_ocp_qp_res.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_d_ocp_qp_sol.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_d_ocp_qp_solver.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_d_ocp_qp_utils.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_d_part_cond.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_d_part_cond_qcqp.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_d_sim_erk.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_d_sim_rk.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_d_tree_ocp_qcqp.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_d_tree_ocp_qcqp_dim.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_d_tree_ocp_qcqp_ipm.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_d_tree_ocp_qcqp_res.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_d_tree_ocp_qcqp_sol.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_d_tree_ocp_qcqp_utils.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_d_tree_ocp_qp.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_d_tree_ocp_qp_dim.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_d_tree_ocp_qp_ipm.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_d_tree_ocp_qp_kkt.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_d_tree_ocp_qp_res.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_d_tree_ocp_qp_sol.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_d_tree_ocp_qp_utils.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_m_dense_qp.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_m_dense_qp_dim.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_m_ocp_qp.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_m_ocp_qp_ipm_hard.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_m_ocp_qp_kkt.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_s_cast_qcqp.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_s_cond.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_s_cond_aux.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_s_cond_qcqp.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_s_core_qp_ipm.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_s_core_qp_ipm_aux.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_s_dense_qcqp.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_s_dense_qcqp_dim.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_s_dense_qcqp_ipm.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_s_dense_qcqp_res.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_s_dense_qcqp_sol.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_s_dense_qcqp_utils.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_s_dense_qp.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_s_dense_qp_dim.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_s_dense_qp_ipm.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_s_dense_qp_kkt.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_s_dense_qp_res.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_s_dense_qp_sol.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_s_dense_qp_utils.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_s_ocp_qcqp.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_s_ocp_qcqp_dim.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_s_ocp_qcqp_ipm.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_s_ocp_qcqp_red.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_s_ocp_qcqp_res.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_s_ocp_qcqp_sol.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_s_ocp_qcqp_utils.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_s_ocp_qp.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_s_ocp_qp_dim.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_s_ocp_qp_ipm.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_s_ocp_qp_kkt.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_s_ocp_qp_red.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_s_ocp_qp_res.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_s_ocp_qp_sol.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_s_ocp_qp_utils.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_s_part_cond.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_s_part_cond_qcqp.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_s_sim_erk.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_s_sim_rk.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_s_tree_ocp_qcqp.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_s_tree_ocp_qcqp_dim.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_s_tree_ocp_qcqp_ipm.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_s_tree_ocp_qcqp_res.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_s_tree_ocp_qcqp_sol.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_s_tree_ocp_qcqp_utils.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_s_tree_ocp_qp.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_s_tree_ocp_qp_dim.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_s_tree_ocp_qp_ipm.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_s_tree_ocp_qp_kkt.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_s_tree_ocp_qp_res.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_s_tree_ocp_qp_sol.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_s_tree_ocp_qp_utils.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_scenario_tree.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_timing.h\n",
      "-- Up-to-date: /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/hpipm_tree.h\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[0mCMake Deprecation Warning at external/hpipm/CMakeLists.txt:36 (cmake_minimum_required):\n",
      "  Compatibility with CMake < 3.10 will be removed from a future version of\n",
      "  CMake.\n",
      "\n",
      "  Update the VERSION argument <min> value.  Or, use the <min>...<max> syntax\n",
      "  to tell CMake that the project requires at least <min> but has been updated\n",
      "  to work with policies introduced by <max> or earlier.\n",
      "\n",
      "\u001b[0m\n",
      "/home/amon/.pyenv/versions/3.9.13/envs/l4acados_dev/lib/python3.9/site-packages/torch/jit/_check.py:178: UserWarning: The TorchScript type system doesn't support instance-level annotations on empty non-base types in `__init__`. Instead, either 1) use a type annotation in the class body, or 2) wrap the type in `torch.jit.Attribute`.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "field AcadosOcpDims.N has been migrated to AcadosOcpOptions.N_horizon. setting AcadosOcpOptions.N_horizon = N. For future comppatibility, please use AcadosOcpOptions.N_horizon directly.CUDA is available! Using GPU cuda.\n",
      "\n",
      "Warning: Please note that the following versions of CasADi are officially supported: 3.4.0 or 3.4.5 or 3.5.1 or 3.5.2 or 3.5.3 or 3.5.4 or 3.5.6 or 3.5.5 or 3.6.0 or 3.6.1 or 3.6.2 or 3.6.3 or 3.6.4 or 3.6.5 or 3.6.6.\n",
      " If there is an incompatibility with the CasADi generated code, please consider changing your CasADi version.\n",
      "Version 3.6.7 currently in use.\n",
      "rm -f libacados_ocp_solver_wr.so\n",
      "rm -f acados_solver_wr.o\n",
      "cc -fPIC -std=c99   -O2 -I/home/amon/Repositories/l4acados/external/acados/include -I/home/amon/Repositories/l4acados/external/acados/include/acados -I/home/amon/Repositories/l4acados/external/acados/include/blasfeo/include -I/home/amon/Repositories/l4acados/external/acados/include/hpipm/include  -c -o acados_solver_wr.o acados_solver_wr.c\n",
      "cc -fPIC -std=c99   -O2 -I/home/amon/Repositories/l4acados/external/acados/include -I/home/amon/Repositories/l4acados/external/acados/include/acados -I/home/amon/Repositories/l4acados/external/acados/include/blasfeo/include -I/home/amon/Repositories/l4acados/external/acados/include/hpipm/include  -c -o wr_model/wr_expl_ode_fun.o wr_model/wr_expl_ode_fun.c\n",
      "cc -fPIC -std=c99   -O2 -I/home/amon/Repositories/l4acados/external/acados/include -I/home/amon/Repositories/l4acados/external/acados/include/acados -I/home/amon/Repositories/l4acados/external/acados/include/blasfeo/include -I/home/amon/Repositories/l4acados/external/acados/include/hpipm/include  -c -o wr_model/wr_expl_vde_forw.o wr_model/wr_expl_vde_forw.c\n",
      "cc -fPIC -std=c99   -O2 -I/home/amon/Repositories/l4acados/external/acados/include -I/home/amon/Repositories/l4acados/external/acados/include/acados -I/home/amon/Repositories/l4acados/external/acados/include/blasfeo/include -I/home/amon/Repositories/l4acados/external/acados/include/hpipm/include  -c -o wr_model/wr_expl_vde_adj.o wr_model/wr_expl_vde_adj.c\n",
      "cc -shared acados_solver_wr.o wr_model/wr_expl_ode_fun.o wr_model/wr_expl_vde_forw.o wr_model/wr_expl_vde_adj.o -o libacados_ocp_solver_wr.so -L/home/amon/Repositories/l4acados/external/acados/lib -lacados -lhpipm -lblasfeo -lm \\\n",
      "-L/home/amon/Repositories/l4acados/examples/l4casadi_vs_l4acados/_l4c_generated -llearned_dyn\n",
      "acados was compiled with OpenMP.\n",
      "Running timing experiment: 0/1000\n",
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      "field AcadosOcpDims.N has been migrated to AcadosOcpOptions.N_horizon. setting AcadosOcpOptions.N_horizon = N. For future comppatibility, please use AcadosOcpOptions.N_horizon directly.\n",
      "Warning: Please note that the following versions of CasADi are officially supported: 3.4.0 or 3.4.5 or 3.5.1 or 3.5.2 or 3.5.3 or 3.5.4 or 3.5.6 or 3.5.5 or 3.6.0 or 3.6.1 or 3.6.2 or 3.6.3 or 3.6.4 or 3.6.5 or 3.6.6.\n",
      " If there is an incompatibility with the CasADi generated code, please consider changing your CasADi version.\n",
      "Version 3.6.7 currently in use.\n",
      "rm -f libacados_ocp_solver_wr_new.so\n",
      "rm -f acados_solver_wr_new.o\n",
      "cc -fPIC -std=c99   -O2 -I/home/amon/Repositories/l4acados/external/acados/include -I/home/amon/Repositories/l4acados/external/acados/include/acados -I/home/amon/Repositories/l4acados/external/acados/include/blasfeo/include -I/home/amon/Repositories/l4acados/external/acados/include/hpipm/include  -c -o acados_solver_wr_new.o acados_solver_wr_new.c\n",
      "cc -fPIC -std=c99   -O2 -I/home/amon/Repositories/l4acados/external/acados/include -I/home/amon/Repositories/l4acados/external/acados/include/acados -I/home/amon/Repositories/l4acados/external/acados/include/blasfeo/include -I/home/amon/Repositories/l4acados/external/acados/include/hpipm/include  -c -o wr_new_model/wr_new_expl_ode_fun.o wr_new_model/wr_new_expl_ode_fun.c\n",
      "cc -fPIC -std=c99   -O2 -I/home/amon/Repositories/l4acados/external/acados/include -I/home/amon/Repositories/l4acados/external/acados/include/acados -I/home/amon/Repositories/l4acados/external/acados/include/blasfeo/include -I/home/amon/Repositories/l4acados/external/acados/include/hpipm/include  -c -o wr_new_model/wr_new_expl_vde_forw.o wr_new_model/wr_new_expl_vde_forw.c\n",
      "cc -fPIC -std=c99   -O2 -I/home/amon/Repositories/l4acados/external/acados/include -I/home/amon/Repositories/l4acados/external/acados/include/acados -I/home/amon/Repositories/l4acados/external/acados/include/blasfeo/include -I/home/amon/Repositories/l4acados/external/acados/include/hpipm/include  -c -o wr_new_model/wr_new_expl_vde_adj.o wr_new_model/wr_new_expl_vde_adj.c\n",
      "cc -shared acados_solver_wr_new.o wr_new_model/wr_new_expl_ode_fun.o wr_new_model/wr_new_expl_vde_forw.o wr_new_model/wr_new_expl_vde_adj.o -o libacados_ocp_solver_wr_new.so -L/home/amon/Repositories/l4acados/external/acados/lib -lacados -lhpipm -lblasfeo -lm \\\n",
      "-L -l\n",
      "acados was compiled with OpenMP.\n",
      "Setting collocation_type to GAUSS_LEGENDRE\n",
      "Setting ext_fun_compile_flags to -O2\n",
      "Setting integrator_type to ERK\n",
      "Setting num_threads_in_batch_solve to 1\n",
      "Setting sim_method_jac_reuse to 0\n",
      "field AcadosOcpDims.N has been migrated to AcadosOcpOptions.N_horizon. setting AcadosOcpOptions.N_horizon = N. For future comppatibility, please use AcadosOcpOptions.N_horizon directly.\n",
      "Getting: N_horizon = 20\n",
      "Getting: Tsim = 0.05\n",
      "Getting: adaptive_levenberg_marquardt_lam = 5.0\n",
      "Getting: adaptive_levenberg_marquardt_mu0 = 0.001\n",
      "Getting: adaptive_levenberg_marquardt_mu_min = 1e-16\n",
      "The option alpha_min is deprecated and has new name: globalization_alpha_min\n",
      "Getting: alpha_min = 0.05\n",
      "The option alpha_reduction is deprecated and has new name: globalization_alpha_reduction\n",
      "Getting: alpha_reduction = 0.7\n",
      "Getting: as_rti_iter = 1\n",
      "Getting: as_rti_level = 4\n",
      "Getting: collocation_type = GAUSS_LEGENDRE\n",
      "Getting: cost_discretization = EULER\n",
      "Getting: custom_templates = []\n",
      "Getting: custom_update_copy = True\n",
      "Getting: custom_update_filename = \n",
      "Getting: custom_update_header_filename = \n",
      "The option eps_sufficient_descent is deprecated and has new name: globalization_line_search_use_sufficient_descent\n",
      "Getting: eps_sufficient_descent = 0\n",
      "Getting: eval_residual_at_max_iter = False\n",
      "Getting: exact_hess_constr = 1\n",
      "Getting: exact_hess_cost = 1\n",
      "Getting: exact_hess_dyn = 1\n",
      "Getting: ext_cost_num_hess = 0\n",
      "Getting: ext_fun_compile_flags = -O2\n",
      "Getting: fixed_hess = 0\n",
      "The option full_step_dual is deprecated and has new name: globalization_full_step_dual\n",
      "Getting: full_step_dual = 0\n",
      "Getting: globalization = FIXED_STEP\n",
      "Getting: globalization_alpha_min = 0.05\n",
      "Getting: globalization_alpha_reduction = 0.7\n",
      "Getting: globalization_eps_sufficient_descent = 0.0001\n",
      "Getting: globalization_fixed_step_length = 1.0\n",
      "Getting: globalization_full_step_dual = 0\n",
      "Getting: globalization_funnel_fraction_switching_condition = 0.001\n",
      "Getting: globalization_funnel_init_increase_factor = 15.0\n",
      "Getting: globalization_funnel_init_upper_bound = 1.0\n",
      "Getting: globalization_funnel_initial_penalty_parameter = 1.0\n",
      "Getting: globalization_funnel_kappa = 0.9\n",
      "Getting: globalization_funnel_sufficient_decrease_factor = 0.9\n",
      "Getting: globalization_line_search_use_sufficient_descent = 0\n",
      "Getting: globalization_use_SOC = 0\n",
      "Getting: hessian_approx = GAUSS_NEWTON\n",
      "Getting: hpipm_mode = BALANCE\n",
      "Getting: integrator_type = ERK\n",
      "Getting: levenberg_marquardt = 0.0\n",
      "The option line_search_use_sufficient_descent is deprecated and has new name: globalization_line_search_use_sufficient_descent\n",
      "Getting: line_search_use_sufficient_descent = 0\n",
      "Getting: log_primal_step_norm = False\n",
      "Getting: model_external_shared_lib_dir = None\n",
      "Getting: model_external_shared_lib_name = None\n",
      "Getting: nlp_solver_ext_qp_res = 0\n",
      "Getting: nlp_solver_max_iter = 1\n",
      "The option nlp_solver_step_length is deprecated and has new name: globalization_fixed_step_length\n",
      "Getting: nlp_solver_step_length = 1.0\n",
      "Getting: nlp_solver_tol_comp = 1e-06\n",
      "Getting: nlp_solver_tol_eq = 1e-06\n",
      "Getting: nlp_solver_tol_ineq = 1e-06\n",
      "Getting: nlp_solver_tol_min_step_norm = 0.0\n",
      "Getting: nlp_solver_tol_stat = 1e-06\n",
      "Getting: nlp_solver_type = SQP_RTI\n",
      "Getting: nlp_solver_warm_start_first_qp = False\n",
      "Getting: num_threads_in_batch_solve = 1\n",
      "Getting: print_level = 0\n",
      "Getting: qp_solver = FULL_CONDENSING_HPIPM\n",
      "Getting: qp_solver_cond_N = 20\n",
      "Getting: qp_solver_cond_block_size = None\n",
      "Getting: qp_solver_cond_ric_alg = 1\n",
      "Getting: qp_solver_iter_max = 50\n",
      "Getting: qp_solver_mu0 = 0.0\n",
      "Getting: qp_solver_ric_alg = 1\n",
      "Getting: qp_solver_tol_comp = None\n",
      "Getting: qp_solver_tol_eq = None\n",
      "Getting: qp_solver_tol_ineq = None\n",
      "Getting: qp_solver_tol_stat = None\n",
      "Getting: qp_solver_warm_start = 0\n",
      "Error getting attribute: '>' not supported between instances of 'NoneType' and 'NoneType'\n",
      "Getting: qp_tol = None\n",
      "Getting: reg_epsilon = 0.0001\n",
      "Getting: regularize_method = NO_REGULARIZE\n",
      "Getting: rti_log_only_available_residuals = 0\n",
      "Getting: rti_log_residuals = 0\n",
      "Getting: set = <bound method AcadosOcpOptions.set of <acados_template.acados_ocp_options.AcadosOcpOptions object at 0x7f20e56d17f0>>\n",
      "Getting: shooting_nodes = [0.   0.05 0.1  0.15 0.2  0.25 0.3  0.35 0.4  0.45 0.5  0.55 0.6  0.65\n",
      " 0.7  0.75 0.8  0.85 0.9  0.95 1.  ]\n",
      "Getting: sim_method_jac_reuse = [0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
      "Getting: sim_method_newton_iter = 3\n",
      "Getting: sim_method_newton_tol = 0.0\n",
      "Getting: sim_method_num_stages = [1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1]\n",
      "Getting: sim_method_num_steps = [1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1]\n",
      "Getting: store_iterates = False\n",
      "Getting: tf = 1.0\n",
      "Getting: time_steps = [0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05\n",
      " 0.05 0.05 0.05 0.05 0.05 0.05]\n",
      "Getting: timeout_heuristic = LAST\n",
      "Getting: timeout_max_time = 0.0\n",
      "Getting: tol = 1e-06\n",
      "Getting: with_adaptive_levenberg_marquardt = False\n",
      "Getting: with_solution_sens_wrt_params = False\n",
      "Getting: with_value_sens_wrt_params = False\n",
      "Setting collocation_type to GAUSS_LEGENDRE\n",
      "Setting ext_fun_compile_flags to -O2\n",
      "Setting integrator_type to ERK\n",
      "Setting num_threads_in_batch_solve to 1\n",
      "Setting sim_method_jac_reuse to 0\n",
      "Warning: Please note that the following versions of CasADi are officially supported: 3.4.0 or 3.4.5 or 3.5.1 or 3.5.2 or 3.5.3 or 3.5.4 or 3.5.6 or 3.5.5 or 3.6.0 or 3.6.1 or 3.6.2 or 3.6.3 or 3.6.4 or 3.6.5 or 3.6.6.\n",
      " If there is an incompatibility with the CasADi generated code, please consider changing your CasADi version.\n",
      "Version 3.6.7 currently in use.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "make: *** No rule to make target 'clean_all'.  Stop.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "cc -fPIC -std=c99   -O2 -I/home/amon/Repositories/l4acados/external/acados/include -I/home/amon/Repositories/l4acados/external/acados/include/acados -I/home/amon/Repositories/l4acados/external/acados/include/blasfeo/include -I/home/amon/Repositories/l4acados/external/acados/include/hpipm/include  -c -o acados_solver_linear_model_with_params_nx2_nu1_np0.o acados_solver_linear_model_with_params_nx2_nu1_np0.c\n",
      "cc -fPIC -std=c99   -O2 -I/home/amon/Repositories/l4acados/external/acados/include -I/home/amon/Repositories/l4acados/external/acados/include/acados -I/home/amon/Repositories/l4acados/external/acados/include/blasfeo/include -I/home/amon/Repositories/l4acados/external/acados/include/hpipm/include  -c -o linear_model_with_params_nx2_nu1_np0_model/linear_model_with_params_nx2_nu1_np0_dyn_disc_phi_fun.o linear_model_with_params_nx2_nu1_np0_model/linear_model_with_params_nx2_nu1_np0_dyn_disc_phi_fun.c\n",
      "cc -fPIC -std=c99   -O2 -I/home/amon/Repositories/l4acados/external/acados/include -I/home/amon/Repositories/l4acados/external/acados/include/acados -I/home/amon/Repositories/l4acados/external/acados/include/blasfeo/include -I/home/amon/Repositories/l4acados/external/acados/include/hpipm/include  -c -o linear_model_with_params_nx2_nu1_np0_model/linear_model_with_params_nx2_nu1_np0_dyn_disc_phi_fun_jac.o linear_model_with_params_nx2_nu1_np0_model/linear_model_with_params_nx2_nu1_np0_dyn_disc_phi_fun_jac.c\n",
      "cc -fPIC -std=c99   -O2 -I/home/amon/Repositories/l4acados/external/acados/include -I/home/amon/Repositories/l4acados/external/acados/include/acados -I/home/amon/Repositories/l4acados/external/acados/include/blasfeo/include -I/home/amon/Repositories/l4acados/external/acados/include/hpipm/include  -c -o linear_model_with_params_nx2_nu1_np0_model/linear_model_with_params_nx2_nu1_np0_dyn_disc_phi_fun_jac_hess.o linear_model_with_params_nx2_nu1_np0_model/linear_model_with_params_nx2_nu1_np0_dyn_disc_phi_fun_jac_hess.c\n",
      "cc -shared acados_solver_linear_model_with_params_nx2_nu1_np0.o linear_model_with_params_nx2_nu1_np0_model/linear_model_with_params_nx2_nu1_np0_dyn_disc_phi_fun.o linear_model_with_params_nx2_nu1_np0_model/linear_model_with_params_nx2_nu1_np0_dyn_disc_phi_fun_jac.o linear_model_with_params_nx2_nu1_np0_model/linear_model_with_params_nx2_nu1_np0_dyn_disc_phi_fun_jac_hess.o -o libacados_ocp_solver_linear_model_with_params_nx2_nu1_np0.so -L/home/amon/Repositories/l4acados/external/acados/lib -lacados -lhpipm -lblasfeo -lm \\\n",
      "-L -l\n",
      "cython \\\n",
      "-o acados_ocp_solver_pyx.c \\\n",
      "-I /home/amon/Repositories/l4acados/external/acados/include/../interfaces/acados_template/acados_template \\\n",
      "/home/amon/Repositories/l4acados/external/acados/include/../interfaces/acados_template/acados_template/acados_ocp_solver_pyx.pyx \\\n",
      "-I /home/amon/Repositories/l4acados/examples/l4casadi_vs_l4acados/c_generated_code \\\n",
      "\n",
      "cc  -c -O2 \\\n",
      "-fPIC \\\n",
      "-o acados_ocp_solver_pyx.o \\\n",
      "-I /home/amon/Repositories/l4acados/external/acados/include/blasfeo/include/ \\\n",
      "-I /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/ \\\n",
      "-I /home/amon/Repositories/l4acados/external/acados/include \\\n",
      "-I /home/amon/.pyenv/versions/3.9.13/envs/l4acados_dev/lib/python3.9/site-packages/numpy/_core/include \\\n",
      "-I /home/amon/.pyenv/versions/3.9.13/include/python3.9 \\\n",
      "acados_ocp_solver_pyx.c \\\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "In file included from /home/amon/.pyenv/versions/3.9.13/envs/l4acados_dev/lib/python3.9/site-packages/numpy/_core/include/numpy/ndarraytypes.h:1909,\n",
      "                 from /home/amon/.pyenv/versions/3.9.13/envs/l4acados_dev/lib/python3.9/site-packages/numpy/_core/include/numpy/ndarrayobject.h:12,\n",
      "                 from /home/amon/.pyenv/versions/3.9.13/envs/l4acados_dev/lib/python3.9/site-packages/numpy/_core/include/numpy/arrayobject.h:5,\n",
      "                 from acados_ocp_solver_pyx.c:1230:\n",
      "/home/amon/.pyenv/versions/3.9.13/envs/l4acados_dev/lib/python3.9/site-packages/numpy/_core/include/numpy/npy_1_7_deprecated_api.h:17:2: warning: #warning \"Using deprecated NumPy API, disable it with \" \"#define NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION\" [-Wcpp]\n",
      "   17 | #warning \"Using deprecated NumPy API, disable it with \" \\\n",
      "      |  ^~~~~~~\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "cc  -shared \\\n",
      "-o acados_ocp_solver_pyx.so \\\n",
      "-Wl,-rpath=/home/amon/Repositories/l4acados/external/acados/lib \\\n",
      "acados_ocp_solver_pyx.o \\\n",
      "/home/amon/Repositories/l4acados/examples/l4casadi_vs_l4acados/c_generated_code/libacados_ocp_solver_linear_model_with_params_nx2_nu1_np0.so \\\n",
      "-L/home/amon/Repositories/l4acados/external/acados/lib -lacados -lhpipm -lblasfeo -lm\n",
      "Warning: Please note that the following versions of CasADi are officially supported: 3.4.0 or 3.4.5 or 3.5.1 or 3.5.2 or 3.5.3 or 3.5.4 or 3.5.6 or 3.5.5 or 3.6.0 or 3.6.1 or 3.6.2 or 3.6.3 or 3.6.4 or 3.6.5 or 3.6.6.\n",
      " If there is an incompatibility with the CasADi generated code, please consider changing your CasADi version.\n",
      "Version 3.6.7 currently in use.\n",
      "rm -f libacados_sim_solver_wr_new.so\n",
      "rm -f acados_sim_solver_wr_new.o\n",
      "rm -f acados_sim_solver_pyx.so\n",
      "rm -f acados_sim_solver_pyx.o\n",
      "cc -fPIC -std=c99   -O2 -I/home/amon/Repositories/l4acados/external/acados/include -I/home/amon/Repositories/l4acados/external/acados/include/acados -I/home/amon/Repositories/l4acados/external/acados/include/blasfeo/include -I/home/amon/Repositories/l4acados/external/acados/include/hpipm/include  -c -o acados_sim_solver_wr_new.o acados_sim_solver_wr_new.c\n",
      "cc -fPIC -std=c99   -O2 -I/home/amon/Repositories/l4acados/external/acados/include -I/home/amon/Repositories/l4acados/external/acados/include/acados -I/home/amon/Repositories/l4acados/external/acados/include/blasfeo/include -I/home/amon/Repositories/l4acados/external/acados/include/hpipm/include  -c -o wr_new_model/wr_new_expl_ode_fun.o wr_new_model/wr_new_expl_ode_fun.c\n",
      "cc -fPIC -std=c99   -O2 -I/home/amon/Repositories/l4acados/external/acados/include -I/home/amon/Repositories/l4acados/external/acados/include/acados -I/home/amon/Repositories/l4acados/external/acados/include/blasfeo/include -I/home/amon/Repositories/l4acados/external/acados/include/hpipm/include  -c -o wr_new_model/wr_new_expl_vde_forw.o wr_new_model/wr_new_expl_vde_forw.c\n",
      "cc -fPIC -std=c99   -O2 -I/home/amon/Repositories/l4acados/external/acados/include -I/home/amon/Repositories/l4acados/external/acados/include/acados -I/home/amon/Repositories/l4acados/external/acados/include/blasfeo/include -I/home/amon/Repositories/l4acados/external/acados/include/hpipm/include  -c -o wr_new_model/wr_new_expl_vde_adj.o wr_new_model/wr_new_expl_vde_adj.c\n",
      "cc -shared acados_sim_solver_wr_new.o wr_new_model/wr_new_expl_ode_fun.o wr_new_model/wr_new_expl_vde_forw.o wr_new_model/wr_new_expl_vde_adj.o -o libacados_sim_solver_wr_new.so -L/home/amon/Repositories/l4acados/external/acados/lib -lacados -lhpipm -lblasfeo -lm\n",
      "cython \\\n",
      "-o acados_sim_solver_pyx.c \\\n",
      "-I /home/amon/Repositories/l4acados/external/acados/include/../interfaces/acados_template/acados_template \\\n",
      "/home/amon/Repositories/l4acados/external/acados/include/../interfaces/acados_template/acados_template/acados_sim_solver_pyx.pyx \\\n",
      "-I /home/amon/Repositories/l4acados/examples/l4casadi_vs_l4acados/c_generated_code \\\n",
      "\n",
      "cc  -c -O2 \\\n",
      "-fPIC \\\n",
      "-o acados_sim_solver_pyx.o \\\n",
      "-I /home/amon/Repositories/l4acados/external/acados/include/blasfeo/include/ \\\n",
      "-I /home/amon/Repositories/l4acados/external/acados/include/hpipm/include/ \\\n",
      "-I /home/amon/Repositories/l4acados/external/acados/include \\\n",
      "-I /home/amon/.pyenv/versions/3.9.13/envs/l4acados_dev/lib/python3.9/site-packages/numpy/_core/include \\\n",
      "-I /home/amon/.pyenv/versions/3.9.13/include/python3.9 \\\n",
      "acados_sim_solver_pyx.c \\\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "In file included from /home/amon/.pyenv/versions/3.9.13/envs/l4acados_dev/lib/python3.9/site-packages/numpy/_core/include/numpy/ndarraytypes.h:1909,\n",
      "                 from /home/amon/.pyenv/versions/3.9.13/envs/l4acados_dev/lib/python3.9/site-packages/numpy/_core/include/numpy/ndarrayobject.h:12,\n",
      "                 from /home/amon/.pyenv/versions/3.9.13/envs/l4acados_dev/lib/python3.9/site-packages/numpy/_core/include/numpy/arrayobject.h:5,\n",
      "                 from acados_sim_solver_pyx.c:1230:\n",
      "/home/amon/.pyenv/versions/3.9.13/envs/l4acados_dev/lib/python3.9/site-packages/numpy/_core/include/numpy/npy_1_7_deprecated_api.h:17:2: warning: #warning \"Using deprecated NumPy API, disable it with \" \"#define NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION\" [-Wcpp]\n",
      "   17 | #warning \"Using deprecated NumPy API, disable it with \" \\\n",
      "      |  ^~~~~~~\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "cc  -shared \\\n",
      "-o acados_sim_solver_pyx.so \\\n",
      "-Wl,-rpath=/home/amon/Repositories/l4acados/external/acados/lib \\\n",
      "acados_sim_solver_pyx.o \\\n",
      "/home/amon/Repositories/l4acados/examples/l4casadi_vs_l4acados/c_generated_code/libacados_sim_solver_wr_new.so \\\n",
      "-L/home/amon/Repositories/l4acados/external/acados/lib -lacados -lhpipm -lblasfeo -lm\n",
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    }
   ],
   "source": [
    "x_l4casadi, opt_times_l4casadi, x_l4acados, opt_times_l4acados = run(\n",
    "    N,\n",
    "    hidden_layers,\n",
    "    solve_steps,\n",
    "    device=device,\n",
    "    num_threads_acados_openmp=num_threads_acados_openmp,\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "opt_times_l4casadi_avg = np.cumsum(opt_times_l4casadi[warmup_iter:]) / np.arange(\n",
    "    1, len(opt_times_l4casadi[warmup_iter:]) + 1\n",
    ")\n",
    "opt_times_l4acados_avg = np.cumsum(opt_times_l4acados[warmup_iter:]) / np.arange(\n",
    "    1, len(opt_times_l4acados[warmup_iter:]) + 1\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "h_l4casadi = plt.plot(\n",
    "    np.arange(warmup_iter, len(opt_times_l4casadi)),\n",
    "    opt_times_l4casadi_avg,\n",
    "    label=\"l4casadi\",\n",
    ")\n",
    "h_l4acados = plt.plot(\n",
    "    np.arange(warmup_iter, len(opt_times_l4casadi)),\n",
    "    opt_times_l4acados_avg,\n",
    "    label=\"l4acados\",\n",
    ")\n",
    "plt.plot(\n",
    "    opt_times_l4casadi,\n",
    "    label=\"l4casadi\",\n",
    "    color=h_l4casadi[0].get_color(),\n",
    "    alpha=0.3,\n",
    ")\n",
    "plt.plot(\n",
    "    opt_times_l4acados,\n",
    "    label=\"l4acados\",\n",
    "    color=h_l4acados[0].get_color(),\n",
    "    alpha=0.3,\n",
    ")\n",
    "plt.axvline(\n",
    "    x=warmup_iter, color=\"k\", linestyle=\"--\", linewidth=1, label=\"warmup\", alpha=0.5\n",
    ")\n",
    "# axes scaling log\n",
    "# plt.xscale(\"log\")\n",
    "plt.yscale(\"log\")\n",
    "# axes title y\n",
    "plt.ylabel(\"Time [s]\")\n",
    "plt.xlabel(\"Iteration\")\n",
    "plt.legend()\n",
    "# plt.ylim([1e-3, 1e-1])\n",
    "plt.grid()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(np.float64(0.016613875351112153),\n",
       " np.float64(0.0023242618188911972),\n",
       " np.float64(7.148022316624338))"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "opt_times_l4casadi_avg[-1], opt_times_l4acados_avg[-1], opt_times_l4casadi_avg[\n",
    "    -1\n",
    "] / opt_times_l4acados_avg[-1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7f20a94553a0>,\n",
       " <matplotlib.lines.Line2D at 0x7f20a9455490>]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(x_l4casadi, linewidth=3)\n",
    "plt.plot(x_l4acados, linewidth=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "np.float64(8.300269194450035e-12)"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.linalg.norm(np.array(x_l4casadi) - np.array(x_l4acados))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7f20a93d2d60>,\n",
       " <matplotlib.lines.Line2D at 0x7f20a93d2e50>]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(np.array(x_l4acados) - np.array(x_l4casadi))"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "zero-order-gpmpc-package-3.10",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
